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Washington, District of Columbia, United States
Remote only
We're looking for a talented and motivated individual to join our team as an AI Engineer. In this role, you'll have the opportunity to work on cutting-edge projects that combine generative AI, agentic systems, machine learning (ML), Large Language Models (LLMs), and prompt engineering to drive innovation. You'll be responsible for designing, developing, and deploying complex solutions in distributed and cloud environments, working with large datasets and text-based data to create innovative technical solutions.
This role is fully remote. On an exception basis may be required to come in once a quarter for planning purposes to Washington, DC.
Responsibilities:
Build and deploy agentic AI systems capable of autonomous decision-making, tool use, and multi-step task execution
Implement end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, deployment and monitoring
Develop LLM-based features such as retrieval-augmented generation (RAG) with citations, text summarization, and embedding pipelines
Design and optimize prompts using prompt engineering techniques for LLMs to achieve desired outcomes
Work with Large Language Models (LLMs) such as Claude, GPT, Gemini, Llama, etc. via APIs or cloud AI platforms to develop solutions for specific tasks
Evaluate and test GenAI features: building test sets, grounding and citation checks, LLM-as-judge scoring, and production quality monitoring
Design, develop, and optimize machine learning models using Python
Deploy and manage solutions in distributed and cloud environments
Collaborate with cross-functional teams to guide business decisions
Job Requirements:
Bachelor's/Master's degree in CS, Data Science, Engineering, or Mathematics field
2+ years of hands-on AI/ML engineering experience, including demonstrable LLM application work
Experience building agentic AI systems (agents with tool/function calling, planning or task decomposition, and multi-step execution), or strong working knowledge of agent architectures and frameworks such as LangGraph, CrewAI, Strands, or AutoGen
Working knowledge of the modern LLM stack: prompt engineering, RAG, embeddings, and structured outputs
Experience in one or more areas of machine learning / artificial intelligence such as classification, clustering, anomaly detection, sentiment analysis, and NLP problems such as text categorization, topic modeling, entity extraction, and text summarization
Ability to think critically about AI or ML system design, including model selection, tradeoffs, and real-world deployment considerations
Experience evaluating AI/ML systems: testing, measuring accuracy, and catching hallucinations
Programming experience using Python and iPython notebooks; good SQL skills
Excellent communication skills to communicate with wide technical and business users
Demonstrate ability to quickly learn new tools and paradigms to deploy cutting edge solutions
Adept at simultaneously working on multiple projects, meeting deadlines, and managing expectations
Preferred Skills:
Experience with prompt engineering techniques such as few-shot learning, zero-shot learning, and chain-of-thought prompting
Experience with cloud platforms (AWS or Azure) and their AI/ML services such as AWS Bedrock, AWS SageMaker, Azure OpenAI, or Azure AI Foundry, and core services such as S3 and Lambda functions
Experience in using deep learning frameworks such as PyTorch or Keras, etc.
Experience in MLOps to operationalize the model building process and monitor models in production
Familiarity with search and vector retrieval such as Elasticsearch, Solr, or vector databases
Familiarity with version control systems, specifically Git, and experience with platforms like Azure DevOps
Familiarity with Linux and cloud CLI tools
Experience creating interactive data visualizations and dashboards in Tableau, Power BI, or other tools
Experience with distributed NoSQL databases such as MongoDB, DynamoDB, etc.
Ability to build full stack systems architected for speed and distributed computing
If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.
For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.
The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
